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caret (version 6.0-80)

Classification and Regression Training

Description

Misc functions for training and plotting classification and regression models.

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install.packages('caret')

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Version

6.0-80

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GPL (>= 2)

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Last Published

May 26th, 2018

Functions in caret (6.0-80)

cars

Kelly Blue Book resale data for 2005 model year GM cars
dhfr

Dihydrofolate Reductase Inhibitors Data
gafs_initial

Ancillary genetic algorithm functions
densityplot.rfe

Lattice functions for plotting resampling results of recursive feature selection
getSamplingInfo

Get sampling info from a train model
recall

Calculate recall, precision and F values
print.train

Print Method for the train Class
print.confusionMatrix

Print method for confusionMatrix
plot.varImp.train

Plotting variable importance measures
lift

Lift Plot
predictors

List predictors used in the model
findLinearCombos

Determine linear combinations in a matrix
maxDissim

Maximum Dissimilarity Sampling
findCorrelation

Determine highly correlated variables
histogram.train

Lattice functions for plotting resampling results
ggplot.train

Plot Method for the train Class
nearZeroVar

Identification of near zero variance predictors
icr.formula

Independent Component Regression
plot.gafs

Plot Method for the gafs and safs Classes
train_model_list

A List of Available Models in train
downSample

Down- and Up-Sampling Imbalanced Data
featurePlot

Wrapper for Lattice Plotting of Predictor Variables
diff.resamples

Inferential Assessments About Model Performance
predict.gafs

Predict new samples
filterVarImp

Calculation of filter-based variable importance
thresholder

Generate Data to Choose a Probability Threshold
dummyVars

Create A Full Set of Dummy Variables
format.bagEarth

Format 'bagEarth' objects
gafs.default

Genetic algorithm feature selection
nullModel

Fit a simple, non-informative model
dotplot.diff.resamples

Lattice Functions for Visualizing Resampling Differences
knnreg

k-Nearest Neighbour Regression
oil

Fatty acid composition of commercial oils
knn3

k-Nearest Neighbour Classification
dotPlot

Create a dotplot of variable importance values
learing_curve_dat

Create Data to Plot a Learning Curve
index2vec

Convert indicies to a binary vector
oneSE

Selecting tuning Parameters
train

Fit Predictive Models over Different Tuning Parameters
mdrr

Multidrug Resistance Reversal (MDRR) Agent Data
ggplot.rfe

Plot RFE Performance Profiles
modelLookup

Tools for Models Available in train
pottery

Pottery from Pre-Classical Sites in Italy
plotClassProbs

Plot Predicted Probabilities in Classification Models
pcaNNet

Neural Networks with a Principal Component Step
preProcess

Pre-Processing of Predictors
predict.knn3

Predictions from k-Nearest Neighbors
varImp.gafs

Variable importances for GAs and SAs
predict.bagEarth

Predicted values based on bagged Earth and FDA models
panel.lift2

Lattice Panel Functions for Lift Plots
varImp

Calculation of variable importance for regression and classification models
panel.needle

Needle Plot Lattice Panel
plsda

Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
summary.bagEarth

Summarize a bagged earth or FDA fit
resampleHist

Plot the resampling distribution of the model statistics
defaultSummary

Calculates performance across resamples
tecator

Fat, Water and Protein Content of Meat Samples
plotObsVsPred

Plot Observed versus Predicted Results in Regression and Classification Models
predict.knnreg

Predictions from k-Nearest Neighbors Regression Model
extractPrediction

Extract predictions and class probabilities from train objects
update.safs

Update or Re-fit a SA or GA Model
safs

Simulated annealing feature selection
rfeControl

Controlling the Feature Selection Algorithms
resamples

Collation and Visualization of Resampling Results
update.train

Update or Re-fit a Model
negPredValue

Calculate sensitivity, specificity and predictive values
prcomp.resamples

Principal Components Analysis of Resampling Results
resampleSummary

Summary of resampled performance estimates
segmentationData

Cell Body Segmentation
safs_initial

Ancillary simulated annealing functions
scat

Morphometric Data on Scat
gafsControl

Control parameters for GA and SA feature selection
spatialSign

Compute the multivariate spatial sign
rfe

Backwards Feature Selection
sbf

Selection By Filtering (SBF)
sbfControl

Control Object for Selection By Filtering (SBF)
var_seq

Sequences of Variables for Tuning
xyplot.resamples

Lattice Functions for Visualizing Resampling Results
trainControl

Control parameters for train
SLC14_1

Simulation Functions
createDataPartition

Data Splitting functions
bag

A General Framework For Bagging
as.matrix.confusionMatrix

Confusion matrix as a table
bagFDA

Bagged FDA
avNNet

Neural Networks Using Model Averaging
classDist

Compute and predict the distances to class centroids
calibration

Probability Calibration Plot
caret-internal

Internal Functions
BloodBrain

Blood Brain Barrier Data
pickSizeBest

Backwards Feature Selection Helper Functions
confusionMatrix

Create a confusion matrix
BoxCoxTrans

Box-Cox and Exponential Transformations
bagEarth

Bagged Earth
caretSBF

Selection By Filtering (SBF) Helper Functions
GermanCredit

German Credit Data
Sacramento

Sacramento CA Home Prices
confusionMatrix.train

Estimate a Resampled Confusion Matrix
cox2

COX-2 Activity Data